Blog Post:Welcome to the SiteCatalyst Finance Fundamentals blog series. In this series we will discuss the implementation basics and example analysis of each fundamental solution that Financial Services customers should consider leveraging. Stay tuned and please feel free to contribute your thoughts/experience as we discuss each solution.
In case you haven't been playing along at home, in our previous post on visitor segmentation, we went over the technical details on how to capture the information we need to be able to report on our website visits by demographic segment. In this post we will show how to upload your key demographic information and pull meaningful reports based on that data.

Step 1: Decide on Demographic Data Set

The very first step in reporting on your customer demographic data is to decide which pieces of data you want to use to build segments or report on. This information is often specific to your KPIs or business need, but often times financial services companies will want to see their data broken out by:

Age Range

Gender

Marital Status

Income Bracket

Length of time as a customer

Number of Products Used/"Share of Wallet"

Occupation

Net Worth/Assets on Deposit

This data is often stored in a back-end database somewhere. It might take some sleuthing to find who to talk to about extracting this data, and some bribes of cupcakes to set up an auto-recurring process with your DBA group.

Step 2: Create the SAINT Fields

We are going to use SAINT to import customer metadata into SiteCatalyst. We need to set up the SAINT fields in the SiteCatalyst Admin Console in order to collect the data. I won't get in to the technical details on how to do so here; if you need assistance, contact your Adobe Consultant or Client Care.

Step 3: Format Your Data for Upload

Apply the SAINT template header files to your sample export in Step 1, making sure the data in the columns match the header. For example, the Age data should have the header of "Age." As long as the Key data is in column A, the other columns can be in any order.
You should now have a .tab file that looks something like this:
Note that the customer ID we captured in part 1 of our post is in Column A, and each row represents one customer.

Step 4: Upload the File into SAINT

Following the steps outlined in the Help Center, upload your file to SAINT. Depending on the number of records and the size of the file, it might take up to 48 hours for the data to be reflected in reports.

Reporting on Demographic Information

Once the SAINT file has processed, the data is now available for reporting. You can now use the uploaded demographic data to break down almost any data point or build segments. The possibilities are nearly endless!
As an example, Adobe Bank wants to make sure that they are adequately cross-promoting other products to existing customer. We can see how different asset levels are completing the account application by running the Assets on Deposit report and pulling in the appropriate Application events:
We can see in the graph above that the users with a net worth over $100k had the highest application completion rate. We can dig deeper to see which products are driving that high number by running a correlation report between Net Worth and the Products report:
You can see that the Mortgage product has the highest completion rate, indicating that high net worth users are more likely to complete a Mortgage application. Perhaps the marketing department should display ads to high net worth clients to encourage them to apply for mortgages.
Have a question about anything related to SiteCatalyst for the Financial Services industry? Do you have any tips or best practices to share? If so, please leave a comment here or send me an email at svertree (at) adobe.com and I will do my best to answer it on this blog so everyone can learn! (Don’t worry – I’ll keep your name and company name confidential).
Author:Susan Vertrees
Date Created:August 5, 2013
Headline:Financial Services Fundamentals: Visitor Segmentation Part 2
Social Counts:
Keywords: #finance #Financial Services #FSI
Publisher:Adobe

Financial Services Fundamentals: Visitor Segmentation Part 2

Welcome to the SiteCatalyst Finance Fundamentals blog series. In this series we will discuss the implementation basics and example analysis of each fundamental solution that Financial Services customers should consider leveraging. Stay tuned and please feel free to contribute your thoughts/experience as we discuss each solution.

In case you haven’t been playing along at home, in our previous post on visitor segmentation, we went over the technical details on how to capture the information we need to be able to report on our website visits by demographic segment. In this post we will show how to upload your key demographic information and pull meaningful reports based on that data.

Step 1: Decide on Demographic Data Set

The very first step in reporting on your customer demographic data is to decide which pieces of data you want to use to build segments or report on. This information is often specific to your KPIs or business need, but often times financial services companies will want to see their data broken out by:

Age Range

Gender

Marital Status

Income Bracket

Length of time as a customer

Number of Products Used/”Share of Wallet”

Occupation

Net Worth/Assets on Deposit

This data is often stored in a back-end database somewhere. It might take some sleuthing to find who to talk to about extracting this data, and some bribes of cupcakes to set up an auto-recurring process with your DBA group.

Step 2: Create the SAINT Fields

We are going to use SAINT to import customer metadata into SiteCatalyst. We need to set up the SAINT fields in the SiteCatalyst Admin Console in order to collect the data. I won’t get in to the technical details on how to do so here; if you need assistance, contact your Adobe Consultant or Client Care.

Step 3: Format Your Data for Upload

Apply the SAINT template header files to your sample export in Step 1, making sure the data in the columns match the header. For example, the Age data should have the header of “Age.” As long as the Key data is in column A, the other columns can be in any order.

You should now have a .tab file that looks something like this:

Note that the customer ID we captured in part 1 of our post is in Column A, and each row represents one customer.

Step 4: Upload the File into SAINT

Following the steps outlined in the Help Center, upload your file to SAINT. Depending on the number of records and the size of the file, it might take up to 48 hours for the data to be reflected in reports.

Reporting on Demographic Information

Once the SAINT file has processed, the data is now available for reporting. You can now use the uploaded demographic data to break down almost any data point or build segments. The possibilities are nearly endless!

As an example, Adobe Bank wants to make sure that they are adequately cross-promoting other products to existing customer. We can see how different asset levels are completing the account application by running the Assets on Deposit report and pulling in the appropriate Application events:

We can see in the graph above that the users with a net worth over $100k had the highest application completion rate. We can dig deeper to see which products are driving that high number by running a correlation report between Net Worth and the Products report:

You can see that the Mortgage product has the highest completion rate, indicating that high net worth users are more likely to complete a Mortgage application. Perhaps the marketing department should display ads to high net worth clients to encourage them to apply for mortgages.

Have a question about anything related to SiteCatalyst for the Financial Services industry? Do you have any tips or best practices to share? If so, please leave a comment here or send me an email at svertree (at) adobe.com and I will do my best to answer it on this blog so everyone can learn! (Don’t worry – I’ll keep your name and company name confidential).

Susan Vertrees

Susan is Financial Services Digital Strategy & Analytics Consultant specializing in SiteCatalyst. She has been with Adobe Consulting for the past 3 years, working on reporting and technical implementations for many Fortune 100 financial services companies. Prior to Adobe, she worked at an award-winning financial services company doing front end web development and user experience design.